Christof Lutteroth is a Professor in the Department of Computer Science at the University of Bath and Director of the REal and Virtual Environments Augmentation Labs (REVEAL). His work focuses on Human-Computer Interaction (HCI) with emphasis on eye-gaze interaction and virtual reality (VR), particularly for health, exercise, and learning applications. He leads multiple research projects funded by organizations like EPSRC, The British Academy, and The Royal Society. Research Interests include developing gaze-controlled interfaces, immersive VR systems, and adaptive UI/UX for fitness and cognitive training. He explores affective design tools, emotion recognition in VR exergaming, and biometric data analysis for health applications. Recent Publications highlight advancements in gaze-based text entry, emotion measurement in VR, AI-driven UI development, and cross-European XR innovation networks. His work spans from foundational HCI methodologies to applied projects in rehabilitation and immersive learning. Grants include EPSRC IAA, British Academy, and Royal Society funding for projects like TapGazer, Hyper-immersive XR, and Affective Design Tools for VR. He collaborates with institutions across Europe through the EMIL project. Laboratory : REVEAL Lab at the University of Bath drives research in immersive technologies, motion analysis, and augmentation of human interaction with digital environments.
Xiaoning Qian is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, where he also serves on the Faculty Advisory Committee for the Texas A&M Institute of Data Science (TAMIDS) and the Executive Committee for the Texas A&M TRIPODS Research Institute for Foundations of Interdisciplinary Data Science (FIDS). He holds a joint appointment in the Applied Math group within the Computational Science Initiative at Brookhaven National Laboratory (BNL). Previously, he was an Associate Professor (2018-2022) and Assistant Professor (2013-2018) at Texas A&M, and an Assistant Professor in the Department of Computer Science and Engineering at the University of South Florida (2009-2013). Dr. Qian received his B.S.E. and M.S.E. degrees from Shanghai Jiaotong University, China, and his M.Ph. and Ph.D. degrees in Electrical Engineering from Yale University. Dr. Qian's research focuses on developing mathematical models and computational algorithms in signal processing, machine learning, and Bayesian methods, particularly in learning, uncertainty quantification, and experimental design. His work spans multiple disciplines, with applications in life sciences and materials science. His research group, the Biomedical Imaging, Sensing, and Genomic Signal Processing Group, actively applies probabilistic models and optimization algorithms to solve complex problems in interdisciplinary domains. His research has evolved from foundational work in bioinformatics and biomedical image processing to more recent applications in materials science and broader AI for science initiatives. Dr. Qian has received numerous scientific awards and recognitions including: National Science Foundation (NSF) CAREER Award Segers Family Dean's Excellence Professorship II in the College of Engineering TEES (Texas A&M Engineering Experiment Station) Senior Faculty Fellow Montague-Center for Teaching Excellence Scholar J. T. Oden Faculty Fellow at the University of Texas, Austin Finalist of the 2023 INFORMS QSR Best Paper Faculty Impact Fellow from the Department of Electrical & Computer Engineering As an advisor , Dr. Qian has mentored numerous graduate students through their PhD and MS programs, with many of his alumni securing positions at prestigious institutions and companies including NIH/NCBI, Microsoft, Baidu Research Lab, and Qualcomm. His research has been supported by multiple grants, including an NSF CAREER award and collaborative research funding from the Information Integration and Informatics program. He is actively recruiting postdoc and graduate student research assistants for projects in machine learning and optimization methods with applications in bioinformatics and materials science. Dr. Qian is involved with several research initiatives including the Objective-Based Uncertainty Quantification (ObjectiveUQ) project, which provides a mathematical framework for integrating prior knowledge and data while enabling effective operational and experimental design under uncertainty. He also co-organizes the Bio-Seminar series for the Biomedical Imaging, Sensing & Genomic Signal Processing group at Texas A&M.
Prof. Carlijn V.C. Bouten is Full Professor of Cell-Matrix Interactions in Cardiovascular Regeneration at Eindhoven University of Technology (TU/e), where she heads the Soft Tissue Engineering & Mechanobiology research group in the Department of Biomedical Engineering. She leads a team of ~40 researchers focusing on cardiovascular tissue regeneration through interdisciplinary approaches. Her research investigates mechanobiological interactions between cells and extracellular environments during tissue growth/regeneration, using multi-scale living model systems. Key innovations include biodegradable heart valve prostheses, hybrid implantable organs, and remote cardiac tissue engineering concepts. She collaborates with material scientists, clinicians, and medtech companies. Education includes an MSc in Functional Anatomy and Biomechanics (Vrije Universiteit Amsterdam, 1991) and PhD (TU/e, 1995), with postdoctoral training at Université Laval and University of London. Her 300+ publications focus on: Cardiovascular tissue engineering Cell-matrix mechanobiology In vitro tissue models Biodegradable implants Hybrid organ development Major scientific honors: ERC Advanced Grant (2022) VICI Grant (2003) Aspasia Career Development Award Coordinator of €18.8M Gravitation Programme Elected member of KNAW and AcademiaNet She leads multiple consortia including RegMed-XB's Cardiac Moonshot and international programs like FET-OPEN 'Hybrid Heart'. Heads TU/e's Soft Tissue Engineering & Mechanobiology lab developing advanced biomaterials and tissue models.
Professor Ali Yapar is a faculty member at Istanbul Technical University in the Electronics and Communication Engineering department. His research focuses on Electromagnetics , Microwave Engineering , and Antenna Technologies , with a particular emphasis on inverse scattering problems and microwave imaging for biomedical applications. He has supervised numerous graduate students and led projects related to breast cancer treatment and rough surface imaging. PhD in Electronics and Communication Engineering from Istanbul Technical University (1997) MSc in Electronics and Communication Engineering (1995) His recent publications analyze advanced techniques for microwave hyperthermia systems, reverse time migration methods, and Newton-based solutions for electromagnetic inverse scattering. Key projects include TUBITAK-funded initiatives on microwave tomography and brain stroke imaging. He serves as a project investigator and executive for electromagnetic research programs. Research areas span Electromagnetic Wave Propagation , Green's Function Applications , and Dielectric Material Analysis . Collaborations include IEEE members and international researchers in computational electromagnetics.
Chris Fuller, Ph.D., is the Samuel Langley Distinguished Professor of Engineering at the College of Engineering , Virginia Tech. He leads the Vibrations and Acoustics Laboratory (VAL) , focusing on active/passive noise control systems, metamaterials, and their application to aerospace, medical devices, and industrial machinery. Education: Ph.D. (1979) and B.E. (1974) from the University of Adelaide, Australia. Research Interests: Structural acoustics, adaptive materials, machine learning in noise prediction, and biomedical acoustics (e.g., neonatal incubators). Awards: ASME Rayleigh Award (2017), NASA Team Achievement Award (1996), and Fellow of the Acoustical Society of America. Recent Publications: Highlight advancements in drone noise reduction using neural networks, metamaterials for HVAC systems, and poro-elastic materials for low-frequency noise control.
Satish C. Boregowda is a Senior Lecturer at the School of Mechanical Engineering, Purdue University in West Lafayette, Indiana. His work focuses on thermodynamics-based analysis of human physiological systems, energy systems engineering, and renewable energy integration. He is affiliated with Purdue's Mechanical Engineering department and maintains an office in POTR 322A. Education & Professional Background : While specific educational details are not provided, his long-term research contributions since 1992 indicate advanced expertise in thermodynamics, biomedical engineering, and energy systems. His career spans over three decades with continuous publication activity. Research Interests : Dr. Boregowda’s core research combines thermodynamics with human physiology, developing metrics like the Objective Stress Index (OSI) to quantify stress responses. His work also addresses energy security through renewable integration, entropy analysis in biological systems, and thermal comfort modeling. He applies constructal theory, fractional calculus, and finite element methods to model human thermal regulation and environmental interactions. Publications Trends : His articles (1992–2025) show sustained focus on: 1) Thermodynamic modeling of human stress and thermal comfort, 2) Renewable energy grid integration strategies, and 3) Advanced computational methods for physiological systems. Recent works emphasize decarbonization pathways and energy policy implications. Grants & Advising : No specific grants or advisees are listed in the provided data. His research likely involves collaborations with aerospace and environmental engineering groups given his work on thermal systems in microgravity and HVAC applications. Labs & Teams : While no specific lab affiliations are mentioned, his research aligns with Purdue’s mechanical engineering initiatives in renewable energy, biomedical engineering, and thermal systems design.
Levi J Hargrove is an Associate Professor at Northwestern University, holding dual appointments in the Department of Physical Medicine and Rehabilitation at the Feinberg School of Medicine and the Department of Biomedical Engineering at the McCormick School of Engineering. He is also a Research Scientist at the Center for Bionic Medicine at Shirley Ryan AbilityLab. His work focuses on developing neural control systems for prosthetic limbs, particularly in myoelectric control and pattern recognition, aiming to create clinically viable solutions for amputees. Education: BScE in Electrical Engineering, University of New Brunswick, 2003 MScE in Electrical Engineering, University of New Brunswick, 2005 PhD in Electrical Engineering, University of New Brunswick, 2008 Research Interests: Signal processing, pattern recognition, myoelectric control of powered prostheses, and neural interfaces for bionic limbs. His lab translates research into clinical applications, such as the first thought-controlled bionic leg and Coapt LLC's pattern recognition systems for upper-limb prosthetics. Awards: 2017 American Academy of Orthotists and Prosthetists Research Award 2014 Department of Defense Outstanding Research Team Award 2015 Collaboration Award from Chicago Innovation Grants: Manages a $25 million portfolio from federal, military, and philanthropic sources. Key projects include NSF-funded research on human-robot interaction and DoD grants for prosthetic innovation. Labs: Leads the Regenstein Foundation Center for Bionic Medicine and collaborates with the Neurorehabilitation and Neural Engineering Lab. His work emphasizes translational research, bridging engineering and clinical practice.
Dr. Scott Hayes is an Associate Professor in the Department of Psychology at The Ohio State University, specializing in Clinical Psychology and Cognitive Neuroscience. He directs the Buckeye Brain Aging Lab (B-BAL) and collaborates with the OSU Center for Brain Health and Performance. His research focuses on neuroimaging techniques to study the effects of physical activity, fitness, and aging on brain structure and function, particularly in memory-related disorders. Education: PhD in Clinical Psychology (Neuropsychology) from the University of Arizona (2006), MA (2002), and BA (1998) with dual honors in Biology and Psychology from Skidmore College. He completed postdoctoral fellowships at Duke University and VA Boston Healthcare System. Research interests include cognitive neuroscience of memory, neural correlates of aging, and applying advanced MRI methods to clinical populations. His work highlights how cardiorespiratory fitness impacts brain health and cognitive decline. Awards include the 2024 Distinguished Teaching Award, Spivack Emerging Leader (2017), and multiple NIH-funded grants. He has authored over 50 peer-reviewed articles, focusing on topics like Alzheimer’s biomarkers, PTSD-related cognitive deficits, and exercise interventions. Labs/Teams: Director of B-BAL, affiliated with OSU Jameson Crane Center for Sports Medicine Institute. Current projects explore brain fitness interventions and resilience in aging populations.
Vivek Boominathan is an Assistant Research Professor in the Department of Electrical and Computer Engineering at Rice University. He is affiliated with the GLEE lab (Geometry, Light, & Imaging lab). His research focuses on computational imaging, combining computer vision, machine learning, applied optics, and nanofabrication to develop innovative imaging systems for applications such as robotics, medical sensing, and virtual/augmented reality. He has contributed to projects like PhlatCam (a lensless camera) and NeuWS (neural wavefront shaping). His work bridges optics, algorithms, and materials science to overcome traditional limitations in imaging systems. Boominathan's research interests include lensless imaging, optical meta-devices, turbulence mitigation, and bio-inspired imaging systems. He has developed systems like Foveated thermal imaging prototypes and real-time lensless microscopes. His lab emphasizes interdisciplinary approaches, integrating hardware design with machine learning. Key projects include: NeuWS: Neural wavefront shaping for imaging through scattering media CoIR: Compressive implicit radar for sensing applications FlatCam and PhlatCam: Ultra-thin lensless imaging devices Bioluminescence imaging in marine species His work has been published in top venues like Science Advances, Optica, and IEEE TPAMI. He collaborates with institutions like NASA JPL and industry partners on applied imaging solutions. Current research trends emphasize sensor-algorithm co-design and high-speed imaging systems for AR/VR applications. Boominathan holds a PhD in Electrical Engineering and has extensive postdoctoral experience in computational imaging. He advises projects in the GLEE lab and mentors students in hardware-software co-design for imaging systems. His lab focuses on translating theoretical innovations into practical devices with commercial potential.
Mohammad F. Islam is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. His research focuses on soft materials, nanomaterials, and their applications in energy, healthcare, and manufacturing. He holds the National Science Foundation CAREER Award, Alfred P. Sloan Research Fellowship, Kavli Frontiers Fellowship, and the George Tallman Ladd Research Award. His work spans advanced materials processing, sustainable energy systems, and self-healing materials. Education: Ph.D. in Physics, Lehigh University (2000) Research Interests: Additive manufacturing and nanofabrication techniques Development of smart materials with self-healing and shape-memory properties Energy storage systems using carbon nanotube aerogels Applications in biomedicine and environmental sustainability Grants & Recognition: Recipient of multiple grants from the Wilton E. Scott Institute for Energy Innovation Co-founder of Watson Nano, commercializing carbon nanotube technologies Labs & Teams: Islam Group at CMU investigating soft matter, nanomaterials, and interdisciplinary applications
Jonathan T. Butcher is a Professor in the Meinig School of Biomedical Engineering at Cornell University. His research focuses on cardiovascular developmental mechanobiology, postnatal valve disease, and heart valve tissue engineering. He holds positions in multiple graduate fields including Biomedical and Biological Sciences and Mechanical Engineering. Dr. Butcher earned his B.S./M.S. in Mechanical and Aerospace Engineering from the University of Virginia (2000), Ph.D. in Mechanical Engineering from Georgia Institute of Technology (2004), and completed a postdoctoral fellowship in Developmental Biology/Pediatric Cardiology at the Medical University of South Carolina (2007). His research integrates experimental, computational, and engineering approaches to study heart valve formation and disease. Key areas include embryonic heart biomechanics, pathological valve remodeling, and 3D-printed tissue constructs. He leads the Butcher Lab, which collaborates on NSF-funded projects like a $3 million initiative on bio-inspired architectural design. Notable awards include being an ASME Fellow (2021), AIMBE Fellow (2019), and recipient of the NSF CAREER Award (2010). He co-mentored doctoral student Alexander Cruz to a 2023 HHMI Gilliam Fellowship. Dr. Butcher’s work bridges biomechanics, genetics, and regenerative medicine. Current efforts aim to translate developmental principles into clinical solutions for valve diseases and engineer living tissues using advanced bioprinting techniques.
Professor Liu Xiaogang is a Distinguished Professor in the Department of Chemistry at the National University of Singapore (NUS). He holds a B. Eng from Beijing Technology and Business University, M.Sc. and Ph.D. degrees in Chemistry from East Carolina University and Northwestern University (USA), respectively, and completed postdoctoral research at MIT. His research focuses on supramolecular coordination chemistry, catalysis, chemical sensors, optogenetics, photon upconversion, and X-ray photonics. Key achievements include pioneering work on metal-organic complexes for optoelectronics and developing advanced X-ray scintillators for medical imaging. Education: B. Eng, Beijing Technology and Business University, China M.Sc. Chemistry, East Carolina University, USA Ph.D. Chemistry, Northwestern University, USA Postdoctoral Associate, Massachusetts Institute of Technology, USA Research Highlights: Professor Liu’s lab has produced groundbreaking advancements in luminescent materials, including directive giant upconversion via supercritical bound states and real-time single-proton counting scintillators. His work bridges chemistry, materials science, and biomedical applications, with notable contributions to photon upconversion, X-ray imaging technologies, and nanotheranostics. Awards: RSC Centenary Prize (2024) President’s Science Award (2016) Advising & Grants: As Principal Investigator of the Liu Lab at NUS, he oversees a dynamic research group focused on cutting-edge nanomaterials and their applications in healthcare and photonics. His grants include support for projects on X-ray luminescence imaging and optogenetic tools. Labs & Teams: The Liu Lab operates within NUS’s Department of Chemistry, collaborating with interdisciplinary teams to advance materials innovation for biomedical and environmental challenges.
Hasan Ayaz, PhD, is an Associate Professor at Drexel University’s School of Biomedical Engineering, Science and Health Systems, and the Department of Psychology in the College of Arts and Sciences. He is a core member of the CONQUER Collaborative and has affiliations with the University of Pennsylvania and Children’s Hospital of Philadelphia. His research focuses on neuroengineering, neuroergonomics, and clinical applications of optical brain imaging, particularly using fNIRS and EEG. He has over 200 publications and has secured funding from federal agencies and industry partners. Dr. Ayaz serves on editorial boards for journals like PLOS One and Frontiers in Human Neuroscience and has organized international neuroergonomics conferences. Education: BSc (Electrical and Electronics Engineering, Boğaziçi University, Turkey), MSc and PhD (Drexel University). Research Interests: Neuroergonomics, functional neuroimaging, biomedical signal processing, neuroengineering, fNIRS, EEG, brain-computer interfaces, and mobile neuroimaging. His work aims to develop next-generation brain imaging technologies for applications ranging from aerospace to healthcare. Key Awards: Received a Wellcome LEAP Grant for Addiction Research in 2024. Grants & Advising: Extensive federal and corporate funding; no explicit student list provided. His research involves interdisciplinary collaborations and clinical partnerships. Labs/Teams: Leads the CONQUER Collaborative and contributes to the Cognitive Neuroengineering group at Drexel.
Dr. Andrew Erwin is an Assistant Professor in Mechanical Engineering at the University of Cincinnati, focusing on robotics, human-robot interaction, and rehabilitation engineering. He holds a PhD and MS from Rice University (2018, 2014) and a BS from the University of Massachusetts Amherst (2012). Prior to UC, he was a postdoc at the University of Southern California and the Jet Propulsion Laboratory. His research explores how forces and movements are executed in healthy individuals, and how robotic devices can assist or restore function post-injury. Key areas include rehabilitation robotics, bio-inspired systems, haptic interfaces, and motor learning. He has received prestigious awards such as the NASA Postdoctoral Program Fellowship (2018) and the IEEE/ASME Transactions on Mechatronics Best Paper Award (2017). Dr. Erwin’s work integrates biomechanics, control systems, and neurophysiology. His lab develops devices like the SE-AssessWrist for wrist assessment and explores planetary seismometers for space missions. He maintains an active Google Scholar profile with over 25 publications. Education: PhD, Mechanical Engineering, Rice University, 2018 MS, Mechanical Engineering, Rice University, 2014 BS, Mechanical Engineering, University of Massachusetts Amherst, 2012 His current research emphasizes curriculum design for robotics learning, human-robot collaboration, and adaptive control systems. He offers a PhD position for Fall 2025 focusing on these areas.
Mustafa Bilgic is a Professor and Chair of the Computer Science Department at Illinois Institute of Technology, where he also directs the Master of Artificial Intelligence program and the Machine Learning Laboratory. His research focuses on machine learning, active learning, explainable AI, and probabilistic graphical models, with applications in healthcare, social media analysis, and biomedical engineering. He has received funding from NSF, NIH, and Samsung, among others. Education: PhD in Computer Science, University of Maryland at College Park (2010) M.S. in Computer Science, University of Maryland at College Park (2006) B.S. in Computer Science, University of Texas at Austin (2004, with High Honors and Special Honors) Research Highlights: Dr. Bilgic's work emphasizes AI ethics, algorithm transparency, and interactive machine learning systems. Notable projects include analyzing political news engagement dynamics and developing frameworks for eliminating explanation noise in AI models. His lab explores tools like OrganoID for tracking organoid growth and IDGI for improving model interpretability. Awards: NSF CAREER Award (2014) ACM SIGKDD Best Student Paper Award (2008) Illinois Tech College of Computing Teaching Excellence Award (2021) Teaching and Leadership: Bilgic teaches advanced courses in AI, machine learning, and data mining. He leads initiatives to bridge AI theory and practical applications, emphasizing interdisciplinary collaboration. His administrative roles include overseeing the AI master’s program and fostering innovation in computing education.
